~/talk

Product Experimentation for Growth

Talkat ProductCon Online September 2020 · on Friday, 2020-09-11· [machine-learning]
links:none on file
slides:none on file

Gives a playbook: start with lots of ideas, run rapid experiments using prototypes and split traffic A/B tests, and limit work to a few track 1–3 core OKRs that must show no harm. Cites WD‑40’s 39 failed attempts before success and Amazon’s marketplace and Prime as experiments that cannibalized but validated demand. Emphasizes capture-and-share learning, compare test vs control cohorts, and prioritize only experiments that move customer usage, retention, revenue or NPS.

AI-written summary · about

  1. 0:00Introduction to growth
  2. 1:54Why experiment matters
  3. 3:37Culture and leadership mindset
  4. 8:11Approach to experimentation
  5. 11:40Learning from experiments
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